Many applications of flow cytometry require either the repetitive handling and analysis of large numbers of samples, particularly in the areas of environmental monitoring, clinical testing and drug discovery, or long-duration sorting operations to obtain purified populations of rare cells for medical use, e.g. Ibrahim and van den Engh, Adv. Biochem. Biotechnol., 106: 19-39 (2007); Johnson et al, Curr. Pharm. Biotechnol., 8: 133-139 (2007); Sugiyama et al, Diabetes Obes. Metab., 10 Suppl 4: 179-185 (2008); Janossy and Shapiro, Cytometry Par B, 74B (Suppl. 1): S6-S10 (2008); Krutzik et al, Nature Chemical Biology, 4: 132-142 (2008); Szczepanski et al, Clin. Chem. Lab. Med., 44: 775-796 (2006); Rutten et al, Cytometry A, 64: 16-26 (2005); Campana, Am. J. Clin. Pathol., 122 (Suppl.): S47-S57 (2004); and the like. High throughput and “walk away” operation of complex flow systems in such contexts are highly desirable, but pose unique process control and engineering challenges, such as (i) preparing and queuing multiple samples for serial analysis, (ii) maintaining alignment and proper functioning of instrument components during prolonged periods of operation to ensure consistency of sample-to-sample measurements or to prevent loss of rare subpopulations, (iii) analysis of samples varying widely in origin and quality, especially in clinical settings, and (iv) recognizing and responding to events affecting the flow system functions, which result in anomalous measurements.
It would be desirable for high throughput and unattended operation of flow systems if such systems had the capability to self-monitor and take automatic corrective action in response to conditions, e.g. clogging of sample tubes, misalignment of illumination beams, degradation of sample, or the like, which may compromise the quality and integrity of the collected data or the purity of isolated cell populations.